RESEARCH ARTICLE


Types of Diagenetic Facies of Tight Sandstone Reservoir and Its Quantitative Identification by Well Log Data



Zhu Peng1, *, Lin Chengyan1, Liu Xiaolei2, He Weicong3, Wang Yulei4, Zhang Hualian5
1 School of Geosciences in China University of Petroleum, Qingdao 266580, China;
2 Sinopec Shengli Oil Field Zhuangxi Researching Center, Dongying 257000, China;
3 BGP Company, CNPC, Zhuozhou 072751, China;
4 Sinopec Shengli Oil Field Drilling Technology Research Institute, Dongying 257000, China;
5 Chongqing Institute of Geology Mineral Resources, Chongqing, 400042, China

Article Information


Identifiers and Pagination:

Year: 2015
Volume: 8
First Page: 308
Last Page: 315
Publisher Id: TOPEJ-8-308
DOI: 10.2174/1874834101508010308

Article History:

Received Date: 22/10/2014
Revision Received Date: 10/1/2014
Acceptance Date: 23/6/2015
Electronic publication date: 19/8/2015
Collection year: 2015

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© 2015 Peng et al.;

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Correspondence: * Address correspondence to this author at the School of Geosciences in China University of Petroleum, Qingdao 266580, China; Tel: +86053286983103; E-mail: pursuit_joe@163.com


Abstract

According to the features of clastic mineral components, diagenesis, diagenetic mineral combination, etc., the tight sandstone reservoir of Esx in block Zhuang62-66 is classified into 5 types of diagenetic facies by the analysis of thin sections, casting thin sections, scanning electron microscopy and core description. Natural gamma (GR), true formation resistivity (Rt), flushed zone formation resistivity (Rxo), compensated neutron (CNL), density (DEN), acoustic (AC) and spontaneous potential (SP) are selected on the basis of comprehensively analyzing the log response mechanism of different diagenesis. The effective log recognition model of diagenetic facies is established on the basis of principal component analysis, five comprehensive variables F~F are built, while F and F account for 91.4% of the total variance, which could replace primitive multi-dimension information. The method is verified through processing of coring wells, thus providing a geological basis for the high quality reservoir prediction of the oilfield in the future.

Keywords: Diagenetic facies, diagenesis, quantitative identification by well log data, principal component analysis.